tidyverse Verbs
Paul
7/16/2020
library(tidyverse)## Warning: package 'tidyverse' was built under R version 4.0.2## -- Attaching packages ----------------- tidyverse 1.3.0 --## v ggplot2 3.3.1 v purrr 0.3.4
## v tibble 3.0.1 v dplyr 1.0.0
## v tidyr 1.1.0 v stringr 1.4.0
## v readr 1.3.1 v forcats 0.5.0## Warning: package 'readr' was built under R version 4.0.2## -- Conflicts -------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(magrittr)##
## Attaching package: 'magrittr'## The following object is masked from 'package:purrr':
##
## set_names## The following object is masked from 'package:tidyr':
##
## extractdatasets::airquality## Ozone Solar.R Wind Temp Month Day
## 1 41 190 7.4 67 5 1
## 2 36 118 8.0 72 5 2
## 3 12 149 12.6 74 5 3
## 4 18 313 11.5 62 5 4
## 5 NA NA 14.3 56 5 5
## 6 28 NA 14.9 66 5 6
## 7 23 299 8.6 65 5 7
## 8 19 99 13.8 59 5 8
## 9 8 19 20.1 61 5 9
## 10 NA 194 8.6 69 5 10
## 11 7 NA 6.9 74 5 11
## 12 16 256 9.7 69 5 12
## 13 11 290 9.2 66 5 13
## 14 14 274 10.9 68 5 14
## 15 18 65 13.2 58 5 15
## 16 14 334 11.5 64 5 16
## 17 34 307 12.0 66 5 17
## 18 6 78 18.4 57 5 18
## 19 30 322 11.5 68 5 19
## 20 11 44 9.7 62 5 20
## 21 1 8 9.7 59 5 21
## 22 11 320 16.6 73 5 22
## 23 4 25 9.7 61 5 23
## 24 32 92 12.0 61 5 24
## 25 NA 66 16.6 57 5 25
## 26 NA 266 14.9 58 5 26
## 27 NA NA 8.0 57 5 27
## 28 23 13 12.0 67 5 28
## 29 45 252 14.9 81 5 29
## 30 115 223 5.7 79 5 30
## 31 37 279 7.4 76 5 31
## 32 NA 286 8.6 78 6 1
## 33 NA 287 9.7 74 6 2
## 34 NA 242 16.1 67 6 3
## 35 NA 186 9.2 84 6 4
## 36 NA 220 8.6 85 6 5
## 37 NA 264 14.3 79 6 6
## 38 29 127 9.7 82 6 7
## 39 NA 273 6.9 87 6 8
## 40 71 291 13.8 90 6 9
## 41 39 323 11.5 87 6 10
## 42 NA 259 10.9 93 6 11
## 43 NA 250 9.2 92 6 12
## 44 23 148 8.0 82 6 13
## 45 NA 332 13.8 80 6 14
## 46 NA 322 11.5 79 6 15
## 47 21 191 14.9 77 6 16
## 48 37 284 20.7 72 6 17
## 49 20 37 9.2 65 6 18
## 50 12 120 11.5 73 6 19
## 51 13 137 10.3 76 6 20
## 52 NA 150 6.3 77 6 21
## 53 NA 59 1.7 76 6 22
## 54 NA 91 4.6 76 6 23
## 55 NA 250 6.3 76 6 24
## 56 NA 135 8.0 75 6 25
## 57 NA 127 8.0 78 6 26
## 58 NA 47 10.3 73 6 27
## 59 NA 98 11.5 80 6 28
## 60 NA 31 14.9 77 6 29
## 61 NA 138 8.0 83 6 30
## 62 135 269 4.1 84 7 1
## 63 49 248 9.2 85 7 2
## 64 32 236 9.2 81 7 3
## 65 NA 101 10.9 84 7 4
## 66 64 175 4.6 83 7 5
## 67 40 314 10.9 83 7 6
## 68 77 276 5.1 88 7 7
## 69 97 267 6.3 92 7 8
## 70 97 272 5.7 92 7 9
## 71 85 175 7.4 89 7 10
## 72 NA 139 8.6 82 7 11
## 73 10 264 14.3 73 7 12
## 74 27 175 14.9 81 7 13
## 75 NA 291 14.9 91 7 14
## 76 7 48 14.3 80 7 15
## 77 48 260 6.9 81 7 16
## 78 35 274 10.3 82 7 17
## 79 61 285 6.3 84 7 18
## 80 79 187 5.1 87 7 19
## 81 63 220 11.5 85 7 20
## 82 16 7 6.9 74 7 21
## 83 NA 258 9.7 81 7 22
## 84 NA 295 11.5 82 7 23
## 85 80 294 8.6 86 7 24
## 86 108 223 8.0 85 7 25
## 87 20 81 8.6 82 7 26
## 88 52 82 12.0 86 7 27
## 89 82 213 7.4 88 7 28
## 90 50 275 7.4 86 7 29
## 91 64 253 7.4 83 7 30
## 92 59 254 9.2 81 7 31
## 93 39 83 6.9 81 8 1
## 94 9 24 13.8 81 8 2
## 95 16 77 7.4 82 8 3
## 96 78 NA 6.9 86 8 4
## 97 35 NA 7.4 85 8 5
## 98 66 NA 4.6 87 8 6
## 99 122 255 4.0 89 8 7
## 100 89 229 10.3 90 8 8
## 101 110 207 8.0 90 8 9
## 102 NA 222 8.6 92 8 10
## 103 NA 137 11.5 86 8 11
## 104 44 192 11.5 86 8 12
## 105 28 273 11.5 82 8 13
## 106 65 157 9.7 80 8 14
## 107 NA 64 11.5 79 8 15
## 108 22 71 10.3 77 8 16
## 109 59 51 6.3 79 8 17
## 110 23 115 7.4 76 8 18
## 111 31 244 10.9 78 8 19
## 112 44 190 10.3 78 8 20
## 113 21 259 15.5 77 8 21
## 114 9 36 14.3 72 8 22
## 115 NA 255 12.6 75 8 23
## 116 45 212 9.7 79 8 24
## 117 168 238 3.4 81 8 25
## 118 73 215 8.0 86 8 26
## 119 NA 153 5.7 88 8 27
## 120 76 203 9.7 97 8 28
## 121 118 225 2.3 94 8 29
## 122 84 237 6.3 96 8 30
## 123 85 188 6.3 94 8 31
## 124 96 167 6.9 91 9 1
## 125 78 197 5.1 92 9 2
## 126 73 183 2.8 93 9 3
## 127 91 189 4.6 93 9 4
## 128 47 95 7.4 87 9 5
## 129 32 92 15.5 84 9 6
## 130 20 252 10.9 80 9 7
## 131 23 220 10.3 78 9 8
## 132 21 230 10.9 75 9 9
## 133 24 259 9.7 73 9 10
## 134 44 236 14.9 81 9 11
## 135 21 259 15.5 76 9 12
## 136 28 238 6.3 77 9 13
## 137 9 24 10.9 71 9 14
## 138 13 112 11.5 71 9 15
## 139 46 237 6.9 78 9 16
## 140 18 224 13.8 67 9 17
## 141 13 27 10.3 76 9 18
## 142 24 238 10.3 68 9 19
## 143 16 201 8.0 82 9 20
## 144 13 238 12.6 64 9 21
## 145 23 14 9.2 71 9 22
## 146 36 139 10.3 81 9 23
## 147 7 49 10.3 69 9 24
## 148 14 20 16.6 63 9 25
## 149 30 193 6.9 70 9 26
## 150 NA 145 13.2 77 9 27
## 151 14 191 14.3 75 9 28
## 152 18 131 8.0 76 9 29
## 153 20 223 11.5 68 9 30air<-datasets::airquality
#skimr::skim(air)# General overview of data
#View(air) #Look at your data
air1<-air %>% select(Day, Month, Temp, Temperature=Temp)#Re-organized the columns and renamed
air2<-air %>%slice(1:10)
air3<-air %>% select(Day, Month,Temp,Temperature=Temp) %>% slice(1:10)
air4<-air %>% select(c(6,5,4), Temperature=Temp) %>%
slice(1:10)air11<-air %>% arrange(Temp)#Ascending order
air12<-air %>%arrange(-Temp)#Descending order
air121<-air %>% arrange(desc(Temp))
air13<-air %>% arrange_at(.vars=c("Temp", "Month"))air21<-air %>% filter(Month==6)
#air21<-air %>% filter_if()airm<-air %>% mutate(time=paste(Day, Month,sep=" ")) airs<-air %>% summarise(mean(Temp))
airs1<-air %>% summarise_all(mean)
airs1<-air%>% drop_na(Ozone, Solar.R) %>% summarise_all(mean)airr <-air %>% rename("Solar_Paul"=Solar.R)ir <- datasets::iris
ir1 <- ir %>% filter(Species=="setosa")
ir_mean <-ir %>% group_by(Species) %>%
summarise_all(mean)
ir_sd<-ir %>% group_by(Species) %>%
summarise_all(sd)
#Use fo rbind and cbind
irr <-rbind(ir_mean,ir_sd)
irc <-cbind(ir_mean, ir_sd)
#mean and sd based on species
ir1<- ir %>% group_by(Species) %>%
filter(Species=="Setosa") %>%
summarise_all(mean) library(ggplot2)
paul<-ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width))+
geom_point()
# Change point size, color and shape
paul1<-ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width))+
geom_point(size = 1.2, color = "steelblue", shape = 21)irir<-ir %>% filter(Species=="setosa") %>%
gather(key = "sepal_petal",value="length_values",-Species)
#Change from character to numeric
mb <-read_csv("mobilemoney_data.csv")## Parsed with column specification:
## cols(
## .default = col_character(),
## hhid = col_double(),
## weight = col_double(),
## account_num = col_double(),
## age = col_double(),
## hh_members = col_double()
## )## See spec(...) for full column specifications.mb1<-mb %>% mutate(GEN=case_when(gender=="male"~0, gender=="female"~1))
#Make your column entries uniform
#library(plyr)
#library(magrittr)
#a<-factor(mb$gender)
#mb$gender <-mapvalues(a, c("male"), c("MALE")) %>%
#mapvalues(a, c("male"), c("MALE")),
library(tidyverse)
library(foreign)
library(magrittr)
library(ggplot2)
library(dplyr)
#use of foreign
fin2 = foreign:: read.spss("financial_data.sav",
use.value.labels = TRUE,
to.data.frame=TRUE)## re-encoding from CP1252ggplot(fin2, aes(x=monthly_income, y=age))+
geom_point(aes(size=Household_size, color="blue"),
alpha=0.75)+
xlab("Monthly income")+
ylab("Age")+
ggtitle("Age, monthly income and household size")
fin2 = foreign:: read.spss("financial_data.sav",
use.value.labels = TRUE,
to.data.frame=TRUE)## re-encoding from CP1252ggplot(fin2, aes(monthly_income, age, color=Household_size))+
geom_point(alpha=1.0)+
xlab("Monthly income")+
ylab("Age")+
ggtitle("Age, Monthly income and household size")
fin2 %>% group_by(gender, credit_usage) %>%
summarise(count=n()) %>%
mutate(percentage=(count/sum(count))*100) %>%
ggplot(aes(x=gender,y=credit_usage,color=percentage))+
geom_point(aes(size=percentage))## `summarise()` regrouping output by 'gender' (override with `.groups` argument)
fin2 %>% group_by(gender, credit_usage) %>%
summarise(count=n()) %>%
mutate(percentage=(count/sum(count))*100) %>%
ggplot(aes(x=credit_usage,y=percentage,fill=gender))+
geom_bar(stat="identity", position="dodge")## `summarise()` regrouping output by 'gender' (override with `.groups` argument)
The bar graph of percentages of the gender in each credit usage category
#geom_boxplot(alpha=1)+ geom_jitter(color=“blue”)
ggplot(fin2,mapping =aes(x=mobile,y=Household_size))+
geom_boxplot(alpha=1)
iris<-datasets::iris
#Sepal Length vs Species
sl<-ggplot(iris, mapping = aes(x=Species, y=Sepal.Length))+
geom_boxplot(alpha=0)
#Sepal width versus species
sw<-ggplot(iris, mapping = aes(x=Species, y=Sepal.Width))+
geom_boxplot(alpha=0)
#Petal length versus species
pl<-ggplot(iris, mapping = aes(x=Species, y=Petal.Length))+
geom_boxplot(alpha=0)
#Petal width versus species
pw<-ggplot(iris, mapping = aes(x=Species, y=Petal.Width))+
geom_boxplot(alpha=0)
library(grid)
library(gridExtra)## Warning: package 'gridExtra' was built under R version 4.0.2##
## Attaching package: 'gridExtra'## The following object is masked from 'package:dplyr':
##
## combinegrid.arrange(sl, sw, pl, ncol =2)
library(plotly)## Warning: package 'plotly' was built under R version 4.0.2##
## Attaching package: 'plotly'## The following object is masked from 'package:ggplot2':
##
## last_plot## The following object is masked from 'package:stats':
##
## filter## The following object is masked from 'package:graphics':
##
## layoutlibrary(gapminder)#Data set called gapminder/ some packages are basically datasets that have been packaged so.## Warning: package 'gapminder' was built under R version 4.0.2gp<-gapminder
df <- gapminder
fig <- df %>%
plot_ly(
x = ~gdpPercap,
y = ~lifeExp,
size = ~pop,
color = ~continent,
frame = ~year,
text = ~country,
hoverinfo = "text",
type = 'scatter',
mode = 'markers'
)
fig <- fig %>% layout(
xaxis = list(
type = "log"
)
)
fig## Warning: `arrange_()` is deprecated as of dplyr 0.7.0.
## Please use `arrange()` instead.
## See vignette('programming') for more help
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.
## Warning: `line.width` does not currently support multiple values.